This goal of this course is to introduce and discuss concepts in research methodology, empirical analysis, and the scientific enterprise in computing. This course will prepare students for conducting research by examining how to plan, conduct, and report on empirical investigations. The course will cover techniques applicable to each of the steps of a research project, including formulating research questions, theory building, data analysis (using both qualitative and quantitative methods), building evidence, assessing validity, and publishing. The course will cover the principal research methods used to study human interaction with computer technology: controlled experiment, case studies, surveys, archival analysis, action research and ethnographies. We will also cover topics in peer review, ethical obligations involving human subjects research, how to give a scientific presentation, and how to write research papers, survey papers, and funding proposals.
Prerequisites
Enrolled as a Graduate Student in CSE or by instructor permission.
Logistics
Class Information
Lecture:
T/R 9:30am – 10:45am
206 Debartolo Hall
Instructor
Dr. Tim Weninger (tweninge@nd.edu)
Office Hours:
Thursday 11:00am-12:00pm in 380 Fitzpatrick Hall
or by appointment
Teaching Assistants
None
Course Format and Activities
| Week | Date | Topic | Discussion Leaders | Pre-Reading | Assignments |
|---|---|---|---|---|---|
| 1 | 01/13 | Introduction | None | ||
| 1 | 01/15 | History and Philosophy of Science | Okasha, Ch 1-3 | ||
| 2 | 01/20 | Critical Reading of Research | Chandrasekharan, Eshwar, et al. “You can’t stay here: The efficacy of reddit’s 2015 ban examined through hate speech.” CSCW (2017): 1-22. | ||
| 2 | 01/22 | Critical Reading of Research | Muchnik, L., Aral, S., & Taylor, S. J. (2013). Social influence bias: A randomized experiment. Science, 341(6146), 647-651. | ||
| 3 | 01/27 | Peer Review | Bohannon, John. “Who’s afraid of peer review?.” Science. (2013): 60-65. Tomkins, A., Zhang, M. and Heavlin, W.D., 2017. Reviewer bias in single-versus double-blind peer review. Proceedings of the National Academy of Sciences, 114(48), pp.12708-12713. http://blog.mrtz.org/2014/12/15/the-nips-experiment.html | ||
| 3 | 01/29 | How to Write a Peer Review | |||
| 4 | 02/03 | Morphology of a Paper and Technical Writing | Discussion Leader: Tim Weninger | Weekly Review: | Weekly Review Due |
| 4 | 02/05 | LaTeX and BibTeX | Weninger Example | ||
| 5 | 02/10 | How to Write your Research | |||
| 5 | 02/12 | How to Write a Survey | |||
| 6 | 02/17 | How to Make a Research Presentation | Discussion Leader: | Weekly Review: | |
| 6 | 02/19 | How to Make a Research Presentation | PPT1 PPT2 PPT3 Discussion Leader: | ||
| 7 | 02/24 | Revising and Publishing Research | Discussion Leader: | Weekly Review: | |
| 7 | 02/26 | Computing as a Discipline | Discussion Leader: | Literature Review Due | |
| 8 | 03/03 | Research Funding and Proposal Writing | Discussion Leader: | Weekly Review: | |
| 8 | 03/05 | IRB, Ethics, and Research Malpractice | Discussion Leader: | ||
| 9 | 03/10 | Spring Break | |||
| 9 | 03/12 | Spring Break | |||
| 10 | 03/17 | Basics of Research, Theory Building | Discussion Leader: | Weekly Review: | |
| 10 | 03/19 | Study Design | Discussion Leader: | Introduction Due | |
| 11 | 03/24 | Experiment Design, Controls, Confounders | Discussion Leader: | Weekly Review: | |
| 11 | 03/26 | Laboratory, quasi and natural experiments | Discussion Leader: | ||
| 12 | 03/31 | What do we mean when we we say that we know a thing? | Discussion Leader: | Weekly Review: | |
| 12 | 04/01 | What do we mean when we we say that we know a thing? pt2 | https://towardsdatascience.com/lessons-from-how-to-lie-with-statistics-57060c0d2f19 | Research Design Due | |
| 13 | 04/07 | Distributions and when statistics lie | Discussion Leader: | Weekly Review: | |
| 13 | 04/09 | Distributions and when statistics lie | Discussion leader: | ||
| 14 | 04/14 | OLS | Discussion Leader: | Weekly Review: | |
| 14 | 04/16 | My results are State of the Art, and other lies we tell ourselves. | Discussion Leader: | ||
| 15 | 04/21 | How to Evaluate AI Systems | Discussion Leader: | Weekly Review: | Final Paper Due |
| 15 | 04/23 | How to Evaluate AI Systems | Discussion Leader: | ||
| 16 | 04/28 | How to Evaluate AI Systems | Discussion Leader: | Weekly Review: | Reviews Due |
| 16 | 04/30 | Reading Day | |||
| 17 | 05/05 | Final Exam | 930-1130am – 206 DeBartolo Hall | Final Exam |
This course will draw materials from research literature as well as lessons accumulated over decades of experience in computing research. Students will attend weekly classes, complete frequent readings and reviews, and formulate a short research review article.
This term we will be using Canvas for class discussion. The system is highly catered to getting you help fast and efficiently from classmates and myself.
Lectures and Class Participation
Students should attend all classes. Effective lectures rely on students’ participation to raise questions and contribute in discussions. We will strive to maintain interactive class discussions if possible.
Questions, Discussions, and Help
If you have any questions or need clarification of class material, what should you do? First, try to post your question to the Canvas forum whenever possible, or otherwise email the instructor. The forum is for you and your peers to discuss class-related materials and to help one another. The forum will be monitored closely, but please be aware that we may not be able to answer all questions on the forum in a timely manner, due to the overwhelming number of questions that such a forum sometimes generates. Also, there are obviously things that are not appropriate for the forum, such as solutions for assignments as well as comments or requests to the staff.
In any case, for more thorough discussion, come to our office hours if you can! Don’t be shy. Use our office hours to their fullest extent to help your study.
Requirements
Coursework
Most class meetings will require pre-reading selected by discussion leaders. Those readings will be discussed during class.
Each weekly reading will result in a short writeup.
Discussion leaders will give a talk at the beginning of each class. Discussion leaders for each week are exempt from the readings.
Signup here: first come first served.
Pre-Candidacy Proposal
A term paper is due at the end of the term with several milestones throughout the semester.
Final Exam
A final exam covering the topics in this course will be administered during finals week.
Grade Breakdown
| Discussion Leaders | 10 |
| Weekly Readings/Reviews | 15 |
| Literature Review | 20 |
| Introduction | 10 |
| Research Design | 5 |
| Final Paper | 10 |
| Peer Review | 5 |
| Final Exam | 25 |
Grades
This table indicates minimum guaranteed grades. Under certain limited circumstances (e.g., an unreasonably hard exam), we may select more generous ranges or scale the scores to adjust.
Total Grade
90-100 A-, A
80-89 B-, B, B+
70-79 C-, C, C+
60-69 D
Polices
Textbooks
Textbooks are required, but generally very cheap or free.
Salganik, Matthew J. Bit by bit: Social research in the digital age. Princeton University Press, 2019.
Okasha, Samir. Philosophy of Science: Very Short Introduction. Oxford University Press, 2016.
Lectures
Students should attend all classes. Effective class meetings rely on students’ participation to raise questions and contribute in discussions. We will strive to maintain interactive class discussions if possible.
Lecture capture and Zoom will not be provided.
Regrading
All requests to change grading of any course work must be submitted to the instructor in writing within one week of when the grades are made available. Requests must be specific and explain why you feel your work deserves additional credit. Do not ask for a regrade until you have studied and understood our sample solution.
Late Work
All scheduled due dates/times are US Eastern Time. Homework is typically due at the beginning of class on the due date, but check each the assignment for specifics.
Due date/time will be strictly enforced. Missing or late and/or unannotated work gets zero credit. If you are unable to complete an assignment due to illness or family emergency, we will understand but please see the instructor as soon as possible to make special arrangements. All such exceptional cases must be fully documented.
Academic Integrity
Notre Dame Students are expected to abide by Academic Code of Honor Pledge:
As a member of the Notre Dame community, I acknowledge that it is my responsibility to learn and abide by principles of intellectual honesty and academic integrity, and therefore I will not participate in or tolerate academic dishonesty.
AI policy:
The discipline of computing typically defers to ACM Guidelines on matters of ethics. For graduate work and scholarship in general this course will use: https://www.acm.org/publications/policies/new-acm-policy-on-authorship
Specifically:
- Authors must be the “creator or originator of an idea” and/or Work
- Authors must make a substantial contribution to the Work
- Authors must be accountable for the work that was done and its presentation in a publication
This implies that the use of advanced AI systems like ChatGPT is expressly permitted for all assignments.
However, special attention must be paid to the final bullet. This implies that any “hallucinations” by any AI system that are submitted as homework (or in any scholarship) are considered intentional misrepresentations (i.e., research malpractice, falsification) of the human author. Dismissal from the program is the default consequence in these events.